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1.
Trends Food Sci Technol ; 104: 219-234, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-1791132

ABSTRACT

BACKGROUND: Garlic (Allium sativum L.) is a common herb consumed worldwide as functional food and traditional remedy for the prevention of infectious diseases since ancient time. Garlic and its active organosulfur compounds (OSCs) have been reported to alleviate a number of viral infections in pre-clinical and clinical investigations. However, so far no systematic review on its antiviral effects and the underlying molecular mechanisms exists. SCOPE AND APPROACH: The aim of this review is to systematically summarize pre-clinical and clinical investigations on antiviral effects of garlic and its OSCs as well as to further analyse recent findings on the mechanisms that underpin these antiviral actions. PubMed, Cochrane library, Google Scholar and Science Direct databases were searched and articles up to June 2020 were included in this review. KEY FINDINGS AND CONCLUSIONS: Pre-clinical data demonstrated that garlic and its OSCs have potential antiviral activity against different human, animal and plant pathogenic viruses through blocking viral entry into host cells, inhibiting viral RNA polymerase, reverse transcriptase, DNA synthesis and immediate-early gene 1(IEG1) transcription, as well as through downregulating the extracellular-signal-regulated kinase (ERK)/mitogen activated protein kinase (MAPK) signaling pathway. The alleviation of viral infection was also shown to link with immunomodulatory effects of garlic and its OSCs. Clinical studies further demonstrated a prophylactic effect of garlic in the prevention of widespread viral infections in humans through enhancing the immune response. This review highlights that garlic possesses significant antiviral activity and can be used prophylactically in the prevention of viral infections.

2.
SSRN; 2022.
Preprint in English | SSRN | ID: ppcovidwho-333342

ABSTRACT

With the spread of COVID-19, many rumors, conspiracy theories, and discourse of fear came into existence. The mainstream media was one of the main sources to educate the masses against such idiosyncrasies and made them save themselves from the disease and its other harmful impacts. In line with this, the study aims at examining COVID-19 awareness campaigns on Pakistani TV channels critically. To evaluate the appropriateness of 24 campaigns/commercials, which were selected through a purposive sampling, a critical multimodal discourse analysis of the campaigns was carried out, using Systemic Functional Grammar proposed by Halliday (2013) (for linguistic resources) along with Kress and van Leeuwen’s Visual Grammar (for nonlinguistic resources). The analysis of campaigns revealed that a few campaigns (e.g., the campaigns of SAMAA TV, PTV, and ISPR) contain sociosemiotic resources (e.g., language, signs, sound, color, picture, animation, actions, etc.) that were more appropriate socio-psychically for Pakistani context, but most campaigns (e.g., the campaigns of Geo TV, ARY, etc.) lack the action-implicative discourse. The study suggests that TV campaigns be culturally and psychologically fit to the context and be action-implicative.

3.
Applied Sciences ; 12(8):3879, 2022.
Article in English | MDPI | ID: covidwho-1785498

ABSTRACT

Recently, the rapid transmission of Coronavirus 2019 (COVID-19) is causing a significant health crisis worldwide. The World Health Organization (WHO) issued several guidelines for protection against the spreading of COVID-19. According to the WHO, the most effective preventive measure against COVID-19 is wearing a mask in public and crowded areas. It is quite difficult to manually monitor and determine people with masks and no masks. In this paper, different deep learning architectures were used for better results evaluations. After extensive experimentation, we selected a custom model having the best performance to identify whether people wear a face mask or not and allowing an easy deployment on a small device such as a Jetson Nano. The experimental evaluation is performed on the custom dataset that is developed from the website (See data collection section) after applying different masks on those images. The proposed model in comparison with other methods produced higher accuracy (99% for training accuracy and 99% for validation accuracy). Moreover, the proposed method can be deployed on resource-constrained devices.

4.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-332610

ABSTRACT

In this paper, we present a framework that automatically labels Latent Dirichlet Allocation (LDA) generated topics using sentiment and aspect terms from COVID-19 tweets to help the end-users by minimizing the cognitive overhead of identifying key topics labels. Social media platforms especially Twitter are considered as one of the most influential sources of information for providing public opinion related to a critical situation like the COVID-19 pandemic. LDA is a popular topic modelling algorithm that extracts hidden themes of documents without assigning a specific label. Thus automatic labelling of LDA-generated topics from COVID-19 tweets is a great challenge instead of following the manual labelling approach to get an overview of wider public opinion. To overcome this problem, in this paper, we propose a framework named \texttt{SATLabel} that effectively identifies significant topic labels using \textit{top unigrams features of sentiment terms and aspect terms clusters from LDA generated topics} of COVID-19 related tweets to uncover various issues related to the COVID-19 pandemic. The experimental results show that our methodology is more effective, simpler, and traces better topic labels compare to the manual topic labelling approach.

5.
Sensors ; 22(7):2602, 2022.
Article in English | MDPI | ID: covidwho-1762313

ABSTRACT

Since December 2019, the COVID-19 pandemic has led to a dramatic loss of human lives and caused severe economic crises worldwide. COVID-19 virus transmission generally occurs through a small respiratory droplet ejected from the mouth or nose of an infected person to another person. To reduce and prevent the spread of COVID-19 transmission, the World Health Organization (WHO) advises the public to wear face masks as one of the most practical and effective prevention methods. Early face mask detection is very important to prevent the spread of COVID-19. For this purpose, we investigate several deep learning-based architectures such as VGG16, VGG19, InceptionV3, ResNet-101, ResNet-50, EfficientNet, MobileNetV1, and MobileNetV2. After these experiments, we propose an efficient and effective model for face mask detection with the potential to be deployable over edge devices. Our proposed model is based on MobileNetV2 architecture that extracts salient features from the input data that are then passed to an autoencoder to form more representations prior to the classification layer. The proposed model also adopts extensive data augmentation techniques (e.g., rotation, flip, Gaussian blur, sharping, emboss, skew, and shear) to increase the number of samples for effective training. The performance of our proposed model is evaluated on three publicly available datasets and achieved the highest performance as compared to other state-of-the-art models.

6.
Psychol Res Behav Manag ; 13: 1047-1055, 2020.
Article in English | MEDLINE | ID: covidwho-1725157

ABSTRACT

PURPOSE: The COVID-19 (coronavirus disease-2019) has been associated with psychological distress during its rapid rise period in Pakistan. The present study aimed to assess the mental health of healthcare workers (HCWs) in the three metropolitan cities of Pakistan. METHODS: A cross-sectional, web-based study was conducted in 276 HCWs from April 10, 2020, to June 5, 2020. Depression, anxiety, and stress scale (DASS-21) were used for the mental health assessment of the HCWs. Multivariable logistic regression analysis (MLRA) was performed to measure the association between the demographics and the occurrence of depression, anxiety, and stress (DAS). RESULTS: The frequency of DAS in the HCWs was 10.1%, 25.4%, and 7.3%, respectively. The MLRA showed that the depression in HCWs was significantly associated with the profession (P<0.001). The anxiety in HCWs was significantly associated with their age (P=0.005), profession (P<0.05), and residence (P<0.05). The stress in HCWs was significantly associated with their age (P<0.05). LIMITATION: This study was conducted in the early phase of the COVID-19 pandemic, when the number of COVID-19 cases was on the rise in Pakistan and it only represents a definite period (April to June 2020). CONCLUSION: The symptoms of DAS are present in the HCWs of Pakistan and to manage the psychological health of HCWs, there is a need for the initiation of psychological well-being programs.

7.
Int J Vitam Nutr Res ; 92(1): 49-66, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1721397

ABSTRACT

The novel coronavirus (SARS-CoV-2) causing COVID-19 disease pandemic has infected millions of people and caused more than thousands of deaths in many countries across the world. The number of infected cases is increasing day by day. Unfortunately, we do not have a vaccine and specific treatment for it. Along with the protective measures, respiratory and/or circulatory supports and some antiviral and retroviral drugs have been used against SARS-CoV-2, but there are no more extensive studies proving their efficacy. In this study, the latest publications in the field have been reviewed, focusing on the modulatory effects on the immunity of some natural antiviral dietary supplements, vitamins and minerals. Findings suggest that several dietary supplements, including black seeds, garlic, ginger, cranberry, orange, omega-3 and -6 polyunsaturated fatty acids, vitamins (e.g., A, B vitamins, C, D, E), and minerals (e.g., Cu, Fe, Mg, Mn, Na, Se, Zn) have anti-viral effects. Many of them act against various species of respiratory viruses, including severe acute respiratory syndrome-related coronaviruses. Therefore, dietary supplements, including vitamins and minerals, probiotics as well as individual nutritional behaviour can be used as adjuvant therapy together with antiviral medicines in the management of COVID-19 disease.


Subject(s)
COVID-19 , Vitamins , Dietary Supplements , Humans , Minerals , SARS-CoV-2
9.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324891

ABSTRACT

The objective of this article is to explore the Information and Communication Technology (ICT) interventions and its strengths, weaknesses, opportunities and threats for the containment of the pandemic spread of novel Coronavirus. The research adopted a qualitative research approach, while the study data were collected through online content review and Focus Group Discussion (FGD). Starting with a preliminary set of about 1200 electronic resources or contents, 56 were selected for review study, applying an inclusion and exclusion criteria. The review study revealed ICT interventions that include websites and dashboards, mobile applications, robotics and drones, artificial intelligence (AI), data analytic, wearable and sensor technology, social media and learning tools, and interactive voice response (IVR) as well as explored their respective usages to combat the pandemic spread of COVID-19. Later, the FGD was replicated with 22 participants and explored the possible strengths, weaknesses, opportunities, and threats (SWOT) of deploying such technologies to fight against the COVID-19 pandemic. This research not only explores the exiting status of ICT interventions to fight with the COVID-19 pandemic but also provides a number of implications for the government, practitioners, doctors, policymakers and researchers for the effective utilization of the existing ICT interventions and for the future potential research and technological development to the containment of the pandemic spread of COVID-19 and future pandemics.

10.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-322567

ABSTRACT

Background: Healthcare workers (HCWs) who are in the frontline during the COVID-19 pandemic are often under significant pressures which may predispose them to mental ill-health. This study aimed to investigate the prevalence of anxiety and depression among HCWs and factors correlated with mental problems during the COVID-19 pandemic in Bangladesh. Methods: A cross-sectional survey was conducted between July and August 2020. A self-reported online questionnaire was utilized to collect data. The survey included questions concerning socio-demographic, lifestyle, and work setting and the Hospital Anxiety and Depression Scale (HADS). Results: Data from 803 HCWs (50.7% male;mean age: 27.3 [SD=6.9];age range: 18-58 years) were included in analyses. Prevalence estimates of anxiety and depression were, respectively, 69.5% and 39.5% for at least borderline abnormal, 41.2% and 15.7% for at least abnormal symptoms. Regression analyses with HADS-score as dependent variable revealed significant (p<0.05) associations with female sex, moderate and poor health status, irregular physical exercising, smoking, having had regrets about their profession because of the pandemic and many unexpected experiences, not updating on the latest COVID-19-related research, experiencing discrimination in the workplace, and facing social problems due to working in a lab or hospital. Conclusions: Symptoms of mental ill-health are prevalent among HCWs during the COVID-19 pandemic in Bangladesh. The findings suggest a need for monitoring and early interventions to help these individuals.

11.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-321162

ABSTRACT

This paper formulates the problem of dynamically identifying key topics with proper labels from COVID-19 Tweets to provide an overview of wider public opinion. Nowadays, social media is one of the best ways to connect people through Internet technology, which is also considered an essential part of our daily lives. In late December 2019, an outbreak of the novel coronavirus, COVID-19 was reported, and the World Health Organization declared an emergency due to its rapid spread all over the world. The COVID-19 epidemic has affected the use of social media by many people across the globe. Twitter is one of the most influential social media services, which has seen a dramatic increase in its use from the epidemic. Thus dynamic extraction of specific topics with labels from tweets of COVID-19 is a challenging issue for highlighting conversation instead of manual topic labeling approach. In this paper, we propose a framework that automatically identifies the key topics with labels from the tweets using the top Unigram feature of aspect terms cluster from Latent Dirichlet Allocation (LDA) generated topics. Our experiment result shows that this dynamic topic identification and labeling approach is effective having the accuracy of 85.48\% with respect to the manual static approach.

12.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-314777

ABSTRACT

The World Health Organization have emphasised that misinformation - spreading rapidly through social media - poses a serious threat to the COVID-19 response. Drawing from theories of health perception and cognitive load, we develop and test a research model hypothesizing why people share unverified COVID-19 information through social media. Our findings suggest a person's trust in online information and perceived information overload are strong predictors of unverified information sharing. Furthermore, these factors, along with a person's perceived COVID-19 severity and vulnerability influence cyberchondria. Females were significantly more likely to suffer from cyberchondria, however, males were more likely to share news without fact checking their source. Our findings suggest that to mitigate the spread of COVID-19 misinformation and cyberchondria, measures should be taken to enhance a healthy skepticism of health news while simultaneously guarding against information overload.

13.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313049

ABSTRACT

The objective of this paper is to synthesize the digital interventions initiatives to fight against COVID-19 in Bangladesh and compare with other countries. In order to obtain our research objective, we conducted a systematic review of the online content. We first reviewed the digital interventions that have been used to fight against COVID-19 across the globe. We then reviewed the initiatives that have been taken place in Bangladesh. Thereafter, we present a comparative analysis between the initiatives taken in Bangladesh and the other countries. Our findings show that while Bangladesh is capable to take benefits of the digital intervention approaches, tighter cooperation between government and private organizations as well as universities would be needed to get the most benefits. Furthermore, the government needs to make sure that the privacy of its citizens are protected.

14.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313048

ABSTRACT

The objective of this research is to explore the existing mobile applications developed for the COVID-19 pandemic. To obtain this research objective, firstly the related applications were selected through the systematic search technique in the popular application stores. Secondly, data related to the app objectives, functionalities provided by the app, user ratings, and user reviews were extracted. Thirdly, the extracted data were analyzed through the affinity diagram, noticing-collecting-thinking, and descriptive analysis. As outcomes, the review provides a state-of-the-art view of mobile apps developed for COVID-19 by revealing nine functionalities or features. It revealed ten factors related to information systems design characteristics that can guide future app design. The review outcome highlights the need for new development and further refinement of the existing applications considering not only the revealed objectives and their associated functionalities, but also revealed design characteristics such as reliability, performance, usefulness, supportive, security, privacy, flexibility, responsiveness, ease of use, and cultural sensitivity.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313047

ABSTRACT

Artificial intelligence (AI) and machine learning (ML) have made a paradigm shift in health care which, eventually can be used for decision support and forecasting by exploring the medical data. Recent studies showed that AI and ML can be used to fight against the COVID-19 pandemic. Therefore, the objective of this review study is to summarize the recent AI and ML based studies that have focused to fight against COVID-19 pandemic. From an initial set of 634 articles, a total of 35 articles were finally selected through an extensive inclusion-exclusion process. In our review, we have explored the objectives/aims of the existing studies (i.e., the role of AI/ML in fighting COVID-19 pandemic);context of the study (i.e., study focused to a specific country-context or with a global perspective);type and volume of dataset;methodology, algorithms or techniques adopted in the prediction or diagnosis processes;and mapping the algorithms/techniques with the data type highlighting their prediction/classification accuracy. We particularly focused on the uses of AI/ML in analyzing the pandemic data in order to depict the most recent progress of AI for fighting against COVID-19 and pointed out the potential scope of further research.

16.
International Journal of Research in Business and Social Science ; 10(8):313-318, 2021.
Article in English | ProQuest Central | ID: covidwho-1662949

ABSTRACT

Received 17 November 2021 Received in rev. form 18 Dec. 2021 Accepted 22 December 2021 Keywords: Covid-19, consumer behavior, generation Z, focus group discussion, new behavior JEL Classification: M30, P36 A B S T R A C T Pandemic crises affect economic conditions both in terms of supply and demand. [...]in the third part, participants were asked to describe the behavioral changes that occurred due to Covid-19. The soaring use of medical devices such as masks, personal protective equipment, and hand sanitizers has increased plastic waste and medical waste. The emergence of Covid-19 makes the world community reduce its activities outside the home, thereby reducing the occurrence of air pollution and greenhouse gas emissions due to vehicle smoke.

17.
Bull Natl Res Cent ; 46(1): 8, 2022.
Article in English | MEDLINE | ID: covidwho-1627798

ABSTRACT

Background: The COVID-19 pandemic jeopardized the traditional academic learning calendars due to the closing of all educational institutions across the globe. To keep up with the flow of learning, most of the educational institutions shifted toward e-learning. However, the students' e-learning preference and e-learning readiness did not identify, particularly among the Bangladeshi female nursing students, where those can pose serious challenges. A cross-sectional study was carried out among the female nursing students between December 26, 2020, and January 11, 2021. A total of 237 students were recruited who have enrolled in e-learning at least the last 30 days of the participation. Multivariable linear regression models were fitted to find the association of students' preference, e-learning readiness domains, and other variables. Results: A cross-sectional study was conducted among the female nursing students to assess perceived e-learning readiness in the subdomains of readiness; availability, technology use, self-confidence, acceptance and training. The findings of the study revealed that the prevalence of preference for e-learning was 43.46%. The students did not prefer e-learning compared to 'prefer group' has significantly less availability of technology (ß = - 3.01, 95% CI - 4.46, - 1.56), less use of technology (ß = - 3.08, 95% CI - 5.11, - 1.06), less self-confidence (ß = - 4.50, 95% CI - 7.02, - 1.98), less acceptance (ß = - 5.96, 95% CI - 7.76, - 4.16) and less training need (ß = - 1.86, 95% CI - 2.67, - 1.06). The age, degree, residence, parents' highest education, having a single room, and having any eye problems were significantly associated with the variation of availability of technology, use of technology, self-confidence, acceptance, and training need of e-learning. Conclusions: The outcomes of the study could be helpful while developing an effective and productive e-learning infrastructure regarding the preparedness of nursing colleges for the continuation of academia in any adverse circumstances like the COVID-19 pandemic.

19.
Accounting, Auditing & Accountability Journal ; 35(1):216-228, 2022.
Article in English | ProQuest Central | ID: covidwho-1596421

ABSTRACT

PurposeThis article aims to examine how non-governmental organisations (NGOs)' narratives portray the vulnerability of workers in global clothing supply chains during the COVID-19 crisis.Design/methodology/approachThe research analyses the rhetoric in global clothing retailers' and NGOs' counter-rhetoric during the first seven months of 2020.FindingsDuring this period, retailers employed rhetorical strategies to legitimise irresponsible actions (corporate hegemony prevailed), while NGOs embraced forms of counter-rhetoric trying to delegitimise the retailers' logic, stressing the role of neoliberalism in worsening the situation.Originality/valueThe authors contribute to the literature by providing new insight into the consequences of COVID-19 for retailers' neoliberal practices and the livelihood of workers in global supply chains. Findings of this study extend authors’ knowledge about retailers' COVID-19 measures: These have contributed to the plights of workers working for their supply factories in the global South.

20.
Chin J Integr Med ; 28(3): 249-256, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1588737

ABSTRACT

OBJECTIVE: To explore potential natural products against severe acute respiratory syndrome coronavirus (SARS-CoV-2) via the study of structural and non-structural proteins of human coronaviruses. METHODS: In this study, we performed an in-silico survey of 25 potential natural compounds acting against SARS-CoV-2. Molecular docking studies were carried out using compounds against 3-chymotrypsin-like protease (3CLPRO), papain-like protease (PLPRO), RNA-dependent RNA polymerase (RdRp), non-structural protein (nsp), human angiotensin converting enzyme 2 receptor (hACE2R), spike glycoprotein (S protein), abelson murine leukemia viral oncogene homolog 1 (ABL1), calcineurin-nuclear factor of activated T-cells (NFAT) and transmembrane protease serine 2. RESULTS: Among the screened compounds, amentoflavone showed the best binding affinity with the 3CLPRO, RdRp, nsp13, nsp15, hACE2R. ABL1 and calcineurin-NFAT; berbamine with hACE2R and ABL1; cepharanthine with nsp10, nsp14, nsp16, S protein and ABL1; glucogallin with nsp15; and papyriflavonol A with PLPRO protein. Other good interacting compounds were juglanin, betulinic acid, betulonic acid, broussooflavan A, tomentin A, B and E, 7-methoxycryptopleurine, aloe emodin, quercetin, tanshinone I, tylophorine and furruginol, which also showed excellent binding affinity towards a number of target proteins. Most of these compounds showed better binding affinities towards the target proteins than the standard drugs used in this study. CONCLUSION: Natural products or their derivatives may be one of the potential targets to fight against SARS-CoV-2.


Subject(s)
Biological Products , COVID-19 , Animals , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use , Biological Products/pharmacology , COVID-19/drug therapy , Humans , Mice , Molecular Docking Simulation , SARS-CoV-2
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